Extension of the general linear model to include prior parameter information

A set of approximations has been applied to allow the inclusion of Gaussian distributed priors for the linear parameters of the general linear model in order that the parameters may be integrated out alongside the Gaussian error noise variance, to give the model evidence and posterior distributions in analytic form. The extended model achieves greater accuracy in parameter estimation and evidence approximation when applied in a Bayesian inference framework, with no increase in computational load.